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Primitive-based 3D Structure Inference from a Single 2D image for Insect Modeling: Towards an Electronic Field Guide for Insect Identification

Primitive-based 3D Structure Inference from a Single 2D Imag...

引用

International Conference on Control, Automation, Robotics and vision

作者： Xiaozheng Zhang Yongsheng Gao Terry Caelli Biosecurity Group Queensland Research Lab National ICT Australia Brisbane Australia Computer Vision and Image Processing Lab Griffith University Brisbane Australia

ISBN: (纸本)9781424478149

3D insect models are useful to overcome viewing angle variations and self-occlusions in computer-assisted insect taxonomy for electronic field guides. The acquisition of 3D information is, however, unreliable due to the flexibility and small size of the insect bodies. This paper explores how to infer 3D insect models from a single 2D insect image, which will assist both insect description and identification. The 3D structure of the insect body is modeled from two geometric primitives, generalized cylinders and deformable ellipsoids. The primitives are fitted and warped based on both edge and medial axis constraints of the 2D image. Individualized 3D models are then built to approximate the insect structure. The proposed approach results in seemingly useful 3D insect models capable of representing the major morphological characteristics for a variety of insects with different body types. This method could be a helpful assistance for computer-assisted insect taxonomy and insect identification by entomologists and the public.

关键词： 3D model insect description structure inference 3D reconstruction

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Car Plate Character Extraction and Recognition Using Stroke Analysis

Car Plate Character Extraction and Recognition Using Stroke ...

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International IEEE Conference on Signal-image Technologies and Internet-Based System

作者： S. Setumin U.U. Sheikh S.A.R Abu-Bakar Computer Vision Video and Image Processing Lab Department of Microelectronics and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

In this paper we address the issue of recognizing nonstandard Malaysian car license plates. These plates contain nonstandard characters such as italic, cursive and connected letters, which most plate recognition systems are unable to recognize. We propose a technique using stroke extraction and analysis to recognize these nonstandard characters. The proposed technique first extracts the contour of the character and then the stroke direction which are used for classification. The advantage of this method is that the system requires no training. From the experiments performed, the method has a correct recognition accuracy of 95% and even works with standard car plates.

关键词： Pixel Character recognition Classification algorithms Licenses Artificial neural networks Training Algorithm design and analysis

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Character-based car plate detection and localization

Character-based car plate detection and localization

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International Symposium on Signal processing and Its Applications (ISSPA)

作者： S. Setumin U.U. Sheikh S.A.R Abu-Bakar Computer Vision Video and Image Processing Research Lab Department of Microelectronics and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

In this paper we address the issue of locating non-standard Malaysian car license plate. Instead of searching the region for the plate, we directly locate the alphanumeric characters of the car plate. In this manner, we remove issues such as plate size variations and plates on black colored vehicles. Our main goal is to locate and extract the alphanumeric characters of Malaysian special plates. These special plates do not follow the normal standard car plates' format as they may contain italic, cursive and connected letters, and of different fonts. Using several parameters such as pixel compactness, angles, and projection histogram, we use ruled-based technique to locate and detect these special characters of the car plates. The results have shown that we are able to automatically locate with an accuracy of 95%.

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Depth estimation with a practical camera

Depth estimation with a practical camera

引用

2009 20th British Machine vision Conference, BMVC 2009

作者： Bhavsar, Arnav V. Rajagopalan, A.N. Image Processing and Computer Vision Lab. Indian Institute of Technology Madras Chennai India

ISBN: (纸本)1901725391

Given an off-the-shelf camera, one has the freedom to move the camera or play around with its intrinsic parameters such as zoom or aperture settings. We propose a framework for depth estimation from a set of calibrated images, captured under general camera motion and parameter variation. Our framework considers the practical trade-offs in a camera and hence essentially generalizes the more constrained areas such as lateral or axial stereo, shape from defocus/focus etc. We discuss practical issues where such an approach becomes important. We pose the problem in a MAP framework and compute the depth estimates efficiently using belief propagation (BP). We also incorporate the visibility consideration to handle occlusions. Moreover, we use the vital cue from color image segmentation to constrain the estimation process. Our results demonstrate the effectiveness of our approach to localize discontinuities and handle low-textured regions. © 2009. The copyright of this document resides with its authors.

关键词： Cameras

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Inpainting in shape from focus: Taking a cue from motion parallax

Inpainting in shape from focus: Taking a cue from motion par...

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2009 20th British Machine vision Conference, BMVC 2009

作者： Sahay, Rajiv R. Rajagopalan, A.N. Image Processing and Computer Vision Lab. Department of Electrical Engineering Indian Institute of Technology Madras Chennai 600 036 India

ISBN: (纸本)1901725391

Shape from focus (SFF) which uses a sequence of space-variantly defocused frames works under the constraint that there is 'no magnification' in the stack. In the presence of sensor damage and/or occlusions, there will be missing data in the observations and SFF cannot recover structure in those regions. In many applications, the capability of filling-in missing data is of critical importance. In this paper, we investigate the effect of motion parallax in SFF and demonstrate the interesting possibility of how it can be judiciously used to jointly inpaint image and depth profiles. When there is relative motion between the 3D specimen and the camera, by virtue of the inherent pixel motion in each of the frames, it is possible to obtain a focused image and depth map of the scene despite missing regions in the observations. © 2009. The copyright of this document resides with its authors.

关键词： Geometrical optics

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labelling color images by modelling the colors density using a linear combination of Gaussians and EM algorithm

Labelling color images by modelling the colors density using...

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IEEE International Conference on image processing

作者： Asem M. Ali Amal A. Farag Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY

Parametric density estimation is widely used to solve many image processing problems. We examined the parametric estimation using linear combination of 1D Gaussians in many works. In this work, we extend our model to estimate density of the colors in color images. We approximate the marginal density of each class in the empirical probability density function by a 3D Gaussian distribution. Then, the deviation between the estimated and the empirical densities is modelled using a linear combination of 3D Gaussians with positive and negative components. We estimate the parameters of this model using our modified EM algorithm. The proposed framework demonstrates very promising experimental results of color images labelling and can be integrated with many other frameworks.

关键词： labeling Color Gaussian processes Function approximation Probability density function image processing Gaussian distribution Parameter estimation image segmentation Gaussian approximation

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Efficient geometric matching with higher-order features

Efficient geometric matching with higher-order features

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作者： Paramanand, C. Rajagopalan, A.N. Image Processing and Computer Vision Lab. Department of Electrical Engineering IIT Madras India

ISBN: (纸本)9781424421756

We propose a new technique in which line segments and elliptical arcs are used as features for recognizing image patterns. By using this approach, the process of locating a model in a given image is efficient since the number of features to be compared is few. We propose distance measures to evaluate the similarity between the features of the model and that of the image. The model transformation parameters are found by searching the transformation space using cell decomposition. © 2008 IEEE.

关键词： Pattern recognition

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On averaging face images for recognition under pose variations

On averaging face images for recognition under pose variatio...

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作者： Zhang, Xiaozheng Zhao, Sanqiang Gao, Yongsheng Computer Vision and Image Processing Lab Institute for Integrated and Intelligent Systems Griffith University Australia

ISBN: (纸本)9781424421756

Recently, psychological studies showed that averaging human face images greatly improves the performance of face recognition under various pose, illumination, expression, and/or aging conditions. This paper investigates quantitatively the mechanism of the face averaging process in face recognition specifically against pose variations. Facilitated with 3D face dataset, the process of face averaging is tested on face images free from human errors and misalignments. Single images are chosen as gallery and the averaged views as probe in all the experiments. Three different scenarios are experimented, i.e., identification using single gallery images, identification using different gallery images, and averaging using unbalanced range of input image. The experimental results show that the averaging process under pose variations is equivalent to generating a face view in an average pose and the improvement in face recognition is subject to the conditions that the gallery pose is close to the average probe pose. © 2008 IEEE.

关键词： Face recognition

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Appearance based 3d object recognition using IPCA-ICA 21

Appearance based 3d object recognition using IPCA-ICA

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21st Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2008

作者： Ananthashayana, V.K. Asha, V. Image Processing and Computer Vision Lab Department of Computer Science and Engineering M.S.Ramaiah Institute of Technology Bangalore India

Fast incremental non Gaussian directional analysis (IPCA-ICA) is proposed as a linear technique for recognition [1]. The basic idea is to compute the principal components as sequence of image vectors incrementally, without estimating the covariance matrix and at the same time transforming these principal components to the independent directions that maximize the non-Gaussianity of the source. In this paper we utilize the IPCA-ICA technique for 3D Object recognition by employing its neural network architecture. We illustrate the potential of IPCA-ICA on a database of 1440 images of 20 different objects captured by CCD camera. The excellent recognition rates achieved in all the performed experiments indicates that the present method is well suited for appearance based 3D object recognition. © 2008 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Principal component analysis

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Density estimation using a new AIC-type criterion and the EM algorithm for a linear combination of Gaussians

Density estimation using a new AIC-type criterion and the EM...

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IEEE International Conference on image processing

作者： Asem M. Ali Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA

We propose a new approach that approximates an empirical probability density function of scalar data with a linear combination of Gaussians (LCG). The proposed algorithm approximates the marginal density of each class using a Gaussian distribution. Number of the classes and their distributions parameters are estimated using a new Akaike Information Criterion (AlC)-type criterion and the Expectation- Maximization (EM) approach. Each class does not follow perfect Gaussian distribution so we refine the initial LCG model using a modified EM algorithm. The modified EM algorithm approximates the marginal density of each class using a LCG with positive and negative components. Experiments in segmenting multimodal medical images show that the developed technique gives promising accurate results.

关键词： Gaussian processes Function approximation Probability density function Gaussian approximation Gaussian distribution Parameter estimation image processing Clustering algorithms image segmentation Probability distribution

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